Face recognition from multi-pose image sequence

A novel approach to face recognition based on a multi-pose image sequence is presented in this paper. In this approach, faces are represented by their pattern vectors (projections to eigenfaces) in eigenspace. Instead of recognising a face from a single view, a sequence of images showing face movement (from left to the right profile) is used for recognition. Pattern vectors corresponding to multiple poses build a trajectory in eigenspace where each trajectory belongs to one face sequence (profile to profile). In the training phase, sequences of poses construct prototype trajectories, and in recognition phase, an unknown face trajectory is compared with prototypes. New matching models are presented and analysed as well as the influence of some parameters on the recognition ratio.